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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: delivery_truck_classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9591836734693877
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# delivery_truck_classification
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0684
- Accuracy: 0.9592
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.86 | 3 | 1.7166 | 0.2245 |
| No log | 1.86 | 6 | 1.5816 | 0.4082 |
| No log | 2.86 | 9 | 1.4084 | 0.5510 |
| No log | 3.86 | 12 | 1.1761 | 0.6327 |
| No log | 4.86 | 15 | 0.9245 | 0.7347 |
| No log | 5.86 | 18 | 0.6986 | 0.7959 |
| 1.608 | 6.86 | 21 | 0.5158 | 0.8367 |
| 1.608 | 7.86 | 24 | 0.3753 | 0.8776 |
| 1.608 | 8.86 | 27 | 0.3092 | 0.8980 |
| 1.608 | 9.86 | 30 | 0.2584 | 0.9388 |
| 1.608 | 10.86 | 33 | 0.2159 | 0.9184 |
| 1.608 | 11.86 | 36 | 0.1908 | 0.9592 |
| 1.608 | 12.86 | 39 | 0.1802 | 0.9592 |
| 0.6473 | 13.86 | 42 | 0.1682 | 0.9592 |
| 0.6473 | 14.86 | 45 | 0.1560 | 0.9592 |
| 0.6473 | 15.86 | 48 | 0.1322 | 0.9592 |
| 0.6473 | 16.86 | 51 | 0.1101 | 0.9592 |
| 0.6473 | 17.86 | 54 | 0.0938 | 0.9592 |
| 0.6473 | 18.86 | 57 | 0.0889 | 0.9796 |
| 0.3855 | 19.86 | 60 | 0.1025 | 0.9796 |
| 0.3855 | 20.86 | 63 | 0.0984 | 0.9796 |
| 0.3855 | 21.86 | 66 | 0.0867 | 0.9592 |
| 0.3855 | 22.86 | 69 | 0.0813 | 0.9592 |
| 0.3855 | 23.86 | 72 | 0.0768 | 0.9592 |
| 0.3855 | 24.86 | 75 | 0.0734 | 0.9796 |
| 0.3855 | 25.86 | 78 | 0.0698 | 0.9796 |
| 0.306 | 26.86 | 81 | 0.0618 | 0.9592 |
| 0.306 | 27.86 | 84 | 0.0547 | 0.9796 |
| 0.306 | 28.86 | 87 | 0.0538 | 0.9592 |
| 0.306 | 29.86 | 90 | 0.0487 | 0.9796 |
| 0.306 | 30.86 | 93 | 0.0447 | 1.0 |
| 0.306 | 31.86 | 96 | 0.0425 | 1.0 |
| 0.306 | 32.86 | 99 | 0.0451 | 1.0 |
| 0.2966 | 33.86 | 102 | 0.0497 | 1.0 |
| 0.2966 | 34.86 | 105 | 0.0558 | 1.0 |
| 0.2966 | 35.86 | 108 | 0.0582 | 0.9796 |
| 0.2966 | 36.86 | 111 | 0.0616 | 0.9592 |
| 0.2966 | 37.86 | 114 | 0.0657 | 0.9592 |
| 0.2966 | 38.86 | 117 | 0.0679 | 0.9592 |
| 0.2535 | 39.86 | 120 | 0.0684 | 0.9592 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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